ArticleJournal of the American Medical Informatics Association : JAMIA2016
Dispatch from the non-HITECH-incented Health IT world: electronic medication history adoption and utilization.
Article in Journal of the American Medical Informatics Association : JAMIA, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Linking Electronic Health Record Prescribing Data and Pharmacy Dispensing Records to Identify Patient-Level Factors Associated With Psychotropic Medication Receipt: Retrospective Study.JMIR medical informatics · 2025Article
- Findings from a National Survey of Medicare Beneficiary Perspectives on the Medicare Part D Medication Therapy Management Standardized Format.Journal of managed care & specialty pharmacy · 2019Article
- Supporting Community Pharmacies with Implementation of a Web-Based Medication Management Application.Applied clinical informatics · 2018Article
- A Statewide Medication Management System: Health Information Exchange to Support Drug Therapy Optimization by Pharmacists across the Continuum of Care.Applied clinical informatics · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo document national trends of electronic medication history use in the ambulatory setting and describe the characteristics and predicting factors of providers who regularly use medication history transaction capabilities through their e-prescribing systems. MATERIALS AND
methodsThe study used provider-initiated medication history data requests, electronically sent over an e-prescribing network from all 50 states and the District of Columbia. Data from 138,000 prescribers were evaluated using multivariate analyses from 2007 to 2013.
resultsMedication history use showed significant growth, increasing from 8 to 850 million history requests during the study period. Prescribers on the network for <5 years had a lower likelihood of requests than those on the network for 5 or more years. Although descriptive analyses showed that prescribers in rural areas were alongside e-prescribing, and requesting medication histories more often than those in large and small cities, these findings were not significant in multivariate analyses. Providers in orthopedic surgery and internal medicine had a higher likelihood of more requests than family practice prescribers, with 12% and 7% higher likelihood, respectively. DISCUSSION: Early adopters of e-prescribing have remained medication history users and have continually increased their volume of requests for medication histories.
conclusionDespite the fact that the use of medication histories through e-prescribing networks in the ambulatory care setting has not been encouraged through federal incentive programs, there has been substantial growth in the use of medication histories offered through e-prescribing networks.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.